1 citations · 1 across the 4 of their papers we have counts for
4 papers
Can We Break Free from Strong Data Augmentations in Self-Supervised Learning?
Shruthi Gowda, Elahe Arani, Bahram Zonooz
Self-supervised learning (SSL) has emerged as a promising solution for addressing the challenge of limited labeled data in deep neural networks (DNNs), offering scalability potenti…
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training
Shruthi Gowda, Bahram Zonooz, Elahe Arani
Adversarial training improves the robustness of neural networks against adversarial attacks, albeit at the expense of the trade-off between standard and robust generalization. To u…
Dual Cognitive Architecture: Incorporating Biases and Multi-Memory Systems for Lifelong Learning
Shruthi Gowda, Bahram Zonooz, Elahe Arani
Artificial neural networks (ANNs) exhibit a narrow scope of expertise on stationary independent data. However, the data in the real world is continuous and dynamic, and ANNs must a…
LSFSL: Leveraging Shape Information in Few-shot Learning
Deepan Chakravarthi Padmanabhan, Shruthi Gowda, Elahe Arani +1
Few-shot learning (FSL) techniques seek to learn the underlying patterns in data using fewer samples, analogous to how humans learn from limited experience. In this limited-data sc…